A QUARTER-CENTURY OF RUSSIAN ACADEMY OF NATURAL SCIENCES (five steps up)
Bibliographic record
Abstract
Summarized the history and formation of the largest Russian public expert organization -the Russian Academy of Natural Sciences, established a turning point for the country's 90 years of the 20th century.Marked and commented on the five stages of the development of the academy: the classic organization of sections, sections of gosprioritetam, thematic sections, regional sections and innovative sections.The motto of the Academy of Natural Sciences -interdisciplinarity and integration of diverse knowledge.The symbol of the Academy is the VI Vernadsky, the Academy is actively promoting Russian cosmism school.RANS initiate registration of scientific discoveries, is widely involved in the educational sector of the country, is the founder in 1994 of the University "Dubna", one of the best universities in the country for the recognition of experts.Publishing RANS -thousands of titles, the Bulletin of Natural Sciences, many sections and departments have their own magazines, including RENSIT.The Academy is widely recruited to participate in international forums (Summits), committees and festivals.As an all-Russian scientific organization, RANS plays an important role one of the cells of civil society, which is consolidating around a large domestic intellectual potential of performing a stabilizing role in the country.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".